Artificial neural networks are changing the world. What are they?

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Since the invention of the computer, there have been people talking about the things that computers will never be able to do. Whether it was beating a grand master at chess or winning on Jeopardy!, these predictions have always been wrong. However, some such nay-saying always had a better grounding in computer science. There were goals that, if you knew how computers worked, you knew they would be virtually impossible to achieve. Recognizing human emotions through facial expressions. Reading a wide variety of cursive handwriting. Correctly identifying the words in spoken language. Driving autonomously through busy streets.

Well, computers are now starting to be able to do all of those things, and quite a bit more. Were the nay-sayers really just too cynical about the true capabilities of digital computers? In a way, no. To solve those monumental challenges, scientists were forced to come up with a whole new type of computer, one based on the structure of the brain. These artificial neural networks (ANNs) only ever exist as a simulation running on a regular digital computer, but what goes on inside that simulation is fundamentally very different from classical computing.

Is an artificial neural network an exercise in computing science? Applied biology? Pure mathematics? Experimental philosophy? It’s all of those things, and much more.

What are ANNs?

Most people already know that the neurons that do the computation in our brain are not organized like the semiconductors in a computer processor, in a linear sequence, attached to the same board, and controlled by one unifying clock cycle. Rather, in the brain each neuron is nominally its own self-contained actor, and it’s wired to most or all of the neurons that physically surround it in highly complex and somewhat unpredictable ways.

What this means is that for a digital computer to achieve an ordered result, it needs one over-arching program to direct it and tell each semiconductor just what to do to contribute toward the overall goal. A brain, on the other hand, unifies billions of tiny, exceedingly simple units that can each have their own programming and make decisions without the need for an outside authority. Each neuron works and interacts with the neurons around it according to its own simple, pre-defined rules.

Most neurons in the brain are connected to several thousand others.

An artificial neural network is (supposed to be) the exact same thing, but simulated with software. In other words, we use a digital computer to run a simulation of a bunch of heavily interconnected little mini-programs which stand in for the neurons of our simulated neural network. Data enters the ANN and has some operation performed on it by the first “neuron,” that operation being determined by how the neuron happens to be programmed to react to data with those specific attributes. It’s then passed on to the next neuron, which is chosen in a similar way, so that another operation can be chosen and performed. There are a finite number of “layers” of these computational neurons, and after moving through them all, an output is produced.

The overall process of turning input into output is an emergent result of the programming of each individual neuron the data touches, and the starting conditions of the data itself. In the the brain, the “starting conditions” are the specific neural signals arriving from the spine, or elsewhere in the brain. In the case of an ANN, they’re whatever we’d like them to be, from the results of a search algorithm to randomly generated numbers to words typed out manually by researchers.

So, to sum up: artificial neural networks are basically simulated brains. But it’s important to note that we can give our software “neurons” basically any programming we want; we can try to set up their rules so their behavior mirrors that of a human brain, but we can also use them to solve problems we could never consider before.

How do ANNs work?

What we’ve described so far is very interesting, but largely useless for computation. That is to say, it’s very scientifically interesting to be able to simulate the cellular structure of the brain, but if I know how to go in and program every little sub-actor such that my inputs are always processed into my desired outputs, then why do I need an ANN at all? Put differently, the nature of an ANN means that intentionally building one to solve a particular problem requires such a deep working knowledge of that problem and its solutions that the ANN itself becomes a bit redundant.

However, there’s a big advantage to working with many simple actors rather than a single complex one: simple actors can self-correct. There have been attempts at self-editing versions of regular software, but it’s artificial neural networks that have taken the concept of machine learning to new heights.

You’ll hear the word “non-deterministic” used to describe the function of a neural network, and that’s in reference to the fact that our software neurons often have weighted statistical likelihoods associated with different outcomes for data; there’s a 40% chance than an input of type A gets passed to this neuron in the next layer, a 60% chance it gets passed to that one instead. These uncertainties quickly add up as neural networks get larger or more elaborately interconnected, so that the exact same starting conditions might lead to many different outcomes or, more importantly, get to the same outcome by many different paths.

So, we introduce the idea of a “learning algorithm.” A simple example is improving efficiency: send the same input into the network over and over and over, and every time it generates the correct output, record the time it took to do so. Some paths from A to B will be naturally more efficient than others, and the learning algorithm can start to reinforce neuronal behaviors that occurred during those runs that proceeded more quickly.

Much more complex ANNs can strive for more complex goals, like correctly identifying the species of animal in a Google image result. The steps in image processing and categorization get adjusted slightly, relying on an evolution-like sifting of random and non-random variation to produce a cat-finding process the ANN’s programmers could never have directly devised.

Non-deterministic ANNs becomes much more deterministic as they restructure themselves to be better at achieving certain results, as determined by the goals of their learning algorithms. This is called “training” the ANN — you train an ANN with examples of its desired function, so it can self-correct based on how well it did on each of these runs. The more you train an ANN, the better it should become at achieving its goals.

Not for a while.

There’s also the idea of “unsupervised” or “adaptive” learning, in which you run the algorithm with no desired outputs in mind, but let it start evaluating results and adjusting itself according to its own… whims? As you might imagine, this isn’t well understood just yet, but it’s also the most likely path down which we might find true AI — or just really, really advanced AI. If we’re ever truly going to send robots out into totally unknown environments to figure out totally unforeseen problems, we’re going to need programs that can assign significance to stimuli on their own, in real time.

That’s where the power of ANNs truly lies: since their structure allows them to make iterative changes to their own programming, they have the ability to find answers that their own creators never could have. Whether you’re a hedge fund, an advertising company, or an oil prospector, the sheer potential of combining the speed of a computer with the versatility of a brain is impossible to ignore. That’s why being able to program “machine learning” algorithms is now one of the most sought-after skill sets in the world.

In the coming century we may very well be less concerned with solving problems than with teaching computers to learn to solve problems for us.

OK, but what can ANNs actually do?

The usefulness of ANNs falls into one of two basic categories: as tools for solving problems that are inherently difficult for both people and digital computers, and as experimental and conceptual models of something — classically, brains. Let’s talk about each one separately.

First, the real reason for interest (and, more importantly, investment) in ANNs is that they can solve problems. Google uses an ANN to learn how to better target “watch next” suggestions after YouTube videos. The scientists at the Large Hadron Collider turned to ANNs to sift the results of their collisions and pull the signature of just one particle out of the larger storm. Shipping companies use them to minimize route lengths over a complex scattering of destinations. Credit card companies use them to identify fraudulent transactions. They’re even becoming accessible to smaller teams and individuals — Amazon, MetaMind, and more are offering tailored machine learning services to anyone for surprisingly modest a fee.

What an ANN thinks dumbbells look like, from training with photos.

Things are just getting started. Google’s been training its photo-analysis algorithms with more and more pictures of animals, and they’re getting pretty good at telling dogs from cats in regular photographs. Both translation and voice synthesis are progressing to the point that we could soon have a babelfish-like device offering natural, real time conversations between people speaking different languages. And, of course, there are the Big Three ostentatious examples that really wear the machine learning on their sleeve: Siri, Now, and Cortana.

The other side of a neural network lies in carefully designing it to mirror the structure of brains. Both our understanding of that structure, and the computational power necessary to simulate it, are nowhere close to what we’d need to do robust brain-science in a computer model. There have been some amazing efforts at simulating certain aspects of certain portions of the brain, but it’s still in the very preliminary stages.

Artificial intelligence, for hire.

One advantage of this approach is that while you can’t (or… shouldn’t) genetically engineer humans to have an experimental change built into their brains, you absolutely can perform such mad-scientist experiments on simulated brains. ANNs can explore a far wider array of possibilities than medicine could ever practically or ethically consider, and they could someday allow scientists to quickly check on more out-there, “I wonder” hypotheses with potentially unexpected results.

When you ask yourself, “Can an artificial neural network do it?” immediately after, ask yourself “Can I do it?” If the answer is yes, then your brain must be capable of doing something that an ANN might one day be able to simulate. On the other hand, there are plenty of things an ANN might one day be able to do that a brain never could.

The potential for ANNs is nearly limitless.

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And an ANN is still dumb as a hammer — no more intelligent or sentient than a toaster that has “learned” to heat a bagel. The only intelligence involved resides safely in the minds of the people who designed it.

Not only are we no where near the singularity, we have no reason to even believe that it is possible with today’s binary logic, silicon based computing appliances. *Believing* otherwise is the stuff of religion and fantasy; not science. It’s like *believing* that a hammer could one day rise up from the dead through some magical and mysterious process that we don’t understand or control and start driving it’s own nails.

Personal opinion — the first step toward real AI is to totally redesign the computer as we know it — possibly making it more organic and somehow endowed with the ability to “grow” it’s own memory cells.

theguy126

The brain obeys physics; no matter how complicated or intelligent it is, it is executing a series of reactions to input or previous neuron activity. A train of thought, a decision, a perception of free will, a range of emotions, is just a bunch of neurons reacting to their previous stimuli. Physics is obviously computable — all that we lack is storage/computing power. Now, I am in agreement that a redesigned computing architecture can rapidly speed up the pace of progress such as IBM’s True North or similar ideas. They will make things much more efficient. But, to say it is *impossible* to create true intelligence on a traditional turing machine, is an argument from ignorance.

Technically it is possible to create a virtual brain from *any* computing substrate even if it’s bouncing rocks powered by water. Of course the latter will be extremely impractically slow, but technically still in line with the laws of physics.

DecksUpMySleeve

I was about to say nearly the same points, thanks for saving my thumbs a lot of work.
I may also add that the subjective uniqueness most adorn the human brain with can be attributed to a willful sense of self-fullfilment through percieving control and freewill within sentience, both of which prove inherently false.

jqpabc123

The brain obeys physics; no matter how complicated or intelligent it is…

Yes it does. The rub is that it may well involve quantum physics that we have yet to discover or fully comprehend and this may not be embodied in any way by a modern computing appliance or it’s binary software. The truth is; at this point in time, we really just don’t know.

But, to say it is *impossible* to create true intelligence on a traditional turing machine, is an argument from ignorance.

It has recently been proven that the simplest possible *universal* Turing machine (capable of performing any computation) can be built from 6 simple switches — possibly made from painted wood and operated by a hand crank.

A modern supercomputer operates electronically and is obviously much, much faster — but it shares the same fundamental design and operates on the same logical model and is thus no more *intelligent* than this simple, hand operated, wooden machine. Anything a supercomputer can do, this simple wooden machine can do — it just takes longer.

So if I understand you correctly, you consider it an “argument from ignorance” to suggest that a few simple pieces of wood can not be made intelligent?

Opinionated Cat Lover

Oh, this is always a fun question. Turing completeness. Is the human mind Turing-Supercomplete (meaning we can never emulate it with a mere ‘Turing complete’ device)? Or is it merely Turing Complete, and the problem is that the computer hardware available right now can’t supply enough raw processing power to emulate a human mind?

I eagerly await the answer on this, but I don’t think a commenter on a 2015 news article about ANNs will be able to supply that answer. :)

jqpabc123

I eagerly await the answer on this…

So you’re waiting for someone to explain why human level intelligence can’t be easily fashioned from a block of wood? Or Legos?

You do realize that current human intelligence as found in nature is ultimately fashioned from dumb chunks of matter and carbon chains, right? Why is it so hard to imagine it can be done in other substrates? Yours is basically an argument from pure intuition, something like “It sounds absurd therefore it’s impossible”

jqpabc123

You do realize that current human intelligence as found in nature is ultimately fashioned from dumb chunks of matter and carbon chains, right?

Yes and since lead and gold are both fashioned from metal atoms, converting one into the other should be a simple matter of finding the right chemical recipe.

/sarcasm

theguy126

Again, what makes you think intelligence *needs* to be constructed from carbon chains in order to work? Just because we happen to be the only living proof of it due to the whims of evolution, does not mean it is the only way.

jqpabc123

Again, what makes you think intelligence *needs* to be constructed from carbon chains in order to work?

What makes you keep insisting that I said this? I have not. Please look up “straw man” and stop wasting your time and mine with attempts to create one.

It may be just be a coincidence that our only available examples of intelligence happen to be carbon based. It may also just be a coincidence that they are organic, living organisms, And it may also just be a coincidence that they do not operate strictly on binary logic and are not strictly digital in nature.

Maybe this is all just an unlikely string of coincidences — or maybe not. We really just don’t know. We are largely ignorant as to the possibilities because we only have one example and no real understanding of *how* to create “intelligence” from scratch.

What I am taking issue with is the faith based leap from ignorance to imminence. The Hollywood induced idea that intelligence is on the verge of somehow emerging from a strictly digital, binary only, non-organic, silicon based machine is pure hyperbole with no real basis in science, logic or reality.

This widespread “belief” in such has grown into a modern day version of alchemy in my opinion.

theguy126

I’ll not argue with your criticism of the belief that we are on the edge of strong AI, since that’s open to debate and it’s hard to predict the future. The specific argument I’m refuting is your intuition that “a few simple blocks of wood can’t be made intelligent” and therefore “a silicon-based computer can’t be made intelligent”. I disagree with both. You did in fact say that a couple comments ago which means you strongly believe there is a fundamental aspect of the way we’re approaching AI that is wrong and can’t be accomplished in “regular computers”, something about needing to take into account quantum physics etc, so yours is a position stronger than simple doubt. All I’m trying to say is, intelligence is nothing more than the complex flow of information that happens to be facilitated by neurons, but might just as easily be facilitated by a simulation of neurons in silicon chips. Of course it doesn’t mean we’re close to understanding how to make true consciousness happen, but neither does it imply such knowledge requires taking into account fancy things like quantum physics.

jqpabc123

All I’m trying to say is, intelligence is nothing more than the complex flow of information that happens to be facilitated by neurons, but might just as easily be facilitated by a simulation of neurons in silicon chips.

All I’m trying to say is, we don’t know enough about neurons, synapses and the communication that occurs between them to be able to simulate a real conscious brain.

Research into brain function is still in it’s infancy. The more we study, the more complex it becomes. Brain activity is both chemical and electrical, digital and analog, synchronous and asynchronous, transmissive and inhibitive. Virtually every known natural phenomenon is involved — all at the same time — with a dash of what appears to be pure randomness (quantum effects?) thrown in for good measure.

Indeed, how close or far we are from reaching this level is largely a matter of opinion, in which yours is just as valid as ours. However, all of the processes you mentioned can be modeled/computed. Earlier you said you think a computer would have to physically “grow” its own memory cells and a regular computer cannot achieve these things (this is the main thing I disagree with). In reality this can be accomplished simply by modeling the events on traditional CPUs down to the molecular level. As well, we probably won’t need to replicate every nook and cranny of the brain’s operation to achieve intelligent machines, any more than we needed to replicate every nook and cranny of a bird’s wing-flapping for flying machines.

jqpabc123

… largely a matter of opinion, in which yours is just as valid as ours.

Here are the pertinent facts (not opinion) at the moment:

1) A binary computer only does math. That is all it does.
2) In order to model anything in a modern binary computer, you first have to define the functionality mathematically. There is no other option.
3) We still can’t define exactly how the brain works. We’re still learning. Almost every serious research attempt reveals that it is more complex than we previously thought. See my reference above.

Here is an opinion:

If nature is any guide, generating “intelligence” from non-living matter is a significantly more difficult problem than generating life from non-living matter (abiogenesis). We have yet to solve this one either.

theguy126

“Just math” is a moot point because it includes capabilities of pretty much anything, since “math” also includes “physics simulations and modeling”.

“Just math” includes the ability to recognize speech, describe images with language, diagnose patients with greater accuracy than doctors, and even learn to play new arcade games by video feed alone, without any prior knowledge or supervision. Are these not signs of “human intelligence” that people were claiming computers would never be able to do mere decades ago?

Artificial neural networks have been conquering domains of “human intelligence” one after another with no sign of stopping anytime soon. You are underestimating the versatility and abstractability of “math” and creating a false dichotomy between “computers” and “everything else”. Any physical aspect of the brain that supposedly requires a “non-math” description (like growing its own memory cells) can actually be modeled/computed in a physics engine, or, if you were, described in “math”. Actually, scientists have already figured out how to describe an entire flatworm in “math” and it behaves exactly like a real flatworm. It’s not an animation; all the neuron activity is being faithfully simulated, which makes it just as alive as a real flatworm.

Holy f***. What a serendipitous find, just written yesterday. And happens to be something I’m very interested in. Thanks

Opinionated Cat Lover

My google-fu is strong.

Now, I’m not sure that 2050 is a realistic date for a Kurzweil singularity, but unlike our blowhard friend here, I’m not going to dismiss it. 2050 will be impressive, that much is sure, but the Singularity will happen when it’s going to happen (or not) regardless of whether or not some people on the ‘net in 2015 agree or disagree. :)

DecksUpMySleeve

Don’t humor him, Quantum physics has nothing to do with the brain. The intricate interworkings of such a small scale only account for a minute precentage of the outcome of predicting their Macro scale components. We can move the data just like a hard drive if we create something equivalent for replication. The only time quantum and string theory come into play is long term adaptive interaction outcomes and variability.
Also there is nothing non-physical about this interaction. We just have yet to monitor it’s scale with enough precision to place principles upon the reaction.

Opinionated Cat Lover

I won’t dismiss quantum physics from the human brain so easily. We really don’t know. But the difference between him and me is that I’m not going to say ‘Oh, we don’t know, so it HAS to be quantum physics.’ Many a futurist has gotten burned by saying something is impossible.

But so far, one key point is that we seem to have emulated a brain in a computer. Sure, it’s just a rat brain, and we’re still working the interactions between neurons and hormones, but…hey, sure seems to be a strike in favor of brains being Turing Complete rather than Turing Super-complete….but let’s not tell him that. ;)

jqpabc123

But the difference between him and me is that I’m not going to say ‘Oh, we don’t know, so it HAS to be quantum physics.’

The real difference between you and me — is reading comprehension and honesty.

You can’t show where I said it HAS to be anything — but nice try.

Until we have a mathematical model and definition of “intelligence”, it’s not possible to make any definitive statement.

Opinionated Cat Lover

Not only are we no where near the singularity, we have no reason to even believe that it is possible with today’s binary logic, silicon based computing appliances

Hmm…sure seems like you are saying it’s impossible right here.

Personal opinion — the first step toward real AI is to totally redesign the computer as we know it — possibly making it more organic and somehow endowed with the ability to “grow” it’s own memory cells.

It even seems like you have a proposed solution.

But you are right. Nowhere have you ever said it absolutely positively cannot happen. Your weaselly escape has increased your blowhard coefficient. Congratulations.

But one thing is absolutely clear here, buddy. You have absolutely no idea what you’re talking about. Have a nice life. ;)

jqpabc123

But you are right. Nowhere have you ever said it absolutely positively cannot happen. Your weaselly escape has increased your blowhard coefficient.

Under standard debate rules, personal insults are an open admission of defeat.

I’ll take it. Thank you and have a nice day.

Opinionated Cat Lover

Oh, how cute. You’re a reject from Spacebattles, too. I’m not sure what you were doing, but debating requires you to acknowledge the other side, so you were NOT debating. Enjoy your win, though, little one. :)

DecksUpMySleeve

We’ve also taught via fMRI. We know how the human brain works.
They took a guy horrible at baseball, who couldn’t hit or throw. Then monitored a professional player during the activities. Then transfered it, and the person poorly coordinated vastly improved on hitting and throwing.
They’ve also done imaging test where they show one man a shape, transfer the brain waves and someone a state away sees the shape.
How if we can transfer coordination and sight is it still an enigma? It’s not.

theguy126

“quantum physics”

Perhaps indeed this is true, but at the moment there is no evidence to suggest that taking quantum physics into account is NECESSARY to make something intelligent. Quantum physics is everywhere, from our brains to the wings of a bird, but we didn’t need quantum physics technology to make airplanes fly. The intelligence in a brain emerges from the myriad of neuronal connections, in which of course quantum physics exists (like it exists everywhere) but nothing suggests it’s the reason for our intelligence.

“So if I understand you correctly, you consider it an “argument from ignorance” to suggest that a few simple pieces of wood can not be made intelligent?”

Yes, actually. You basically just reversed my argument. I already said earlier that a computer made of bouncing rocks powered by water can theoretically be as intelligent as a supercomputer, only magnitudes slower. So to say a simple turing machine cannot be made intelligent, is equivalent to saying a supercomputer cannot. And, saying a supercomputer cannot, is equivalent to saying a human brain cannot (as long as you are on board with me that all physics is computable, and therefore you can theoretically run the equivalent of a human brain in a computer). Of course, it’s an entirely different matter to say it will never be PRACTICALLY intelligent, because we can both agree a computer made of wood planks will probably never be fast enough to do anything useful.

jqpabc123

… but at the moment there is no evidence to suggest that taking quantum physics into account is NECESSARY to make something intelligent.

And there is no evidence that it is not. As I said above, we really just don’t know at this point since we have never actually built “intelligence”.

Until we have a mathematical model and definition of “intelligence”, it’s not possible to make any definitive statement. In the meantime, it is unreasonable and unscientific to expect real “intelligence” to just magically emerge from a Turing machine. It’s less sensical than giving a monkey a keyboard and expecting Shakespeare to pop out some day.

And yet lots of people have “faith” that it is imminent. And the most disappointing thing to me is the fact that some of these people appear to be somewhat technically competent.

theguy126

Actually, it’s the most technically competent people who tend to believe it is possible. The people who don’t, tend to be less technically competent.

We already have “intelligent” machines. They can do things that no human would’ve thought a computer could’ve done 50 years ago. They can look at a picture and tell us it’s of “two pizzas sitting on a stove oven”. There is nothing to suggest that quantum physics is required for these thought processes. Nor is there anything to suggest that quantum physics is needed for higher level awareness/consciousness. Nor would quantum physics shed ANY light on the “hard problem of consciousness” which I happen to believe and understand is actually a hard problem.

Perhaps 50 years ago you would’ve been the person who said “you can’t make a computer interpret images with simply a turing machine; it needs quantum mechanics etc…”

You are now simply playing the game of “goalpost-moving”. And gradually we will show you that no matter where you move the goalpost, AI will always catch up.

Opinionated Cat Lover

I see him arguing with an AI in the future, saying it can’t possibly be self-aware.

Bonus points if he argues against the notion after being Uploaded! :D

But I’ll stop being silly now. :)

Francis Short Jr

Your saying everything in the physical universe can be explained?

theguy126

No, such an assumption is not necessary for my viewpoint to be true. You could’ve used this same argument against a person claiming that it’s possible for humans to manufacture stars because it happens in nature, or even a person claiming that it’s possible for humans to achieve heavier-than-air flight because look at the birds (and in fact we did that with airplanes). The fact remains: If it exists in nature, it will probably *eventually* be possible to manufacture. And probably it would be much easier replicating only the structure/network/behavior of the neurons rather than trying to simulate every single chemical reaction down to the molecular and quantum level.

DecksUpMySleeve

In eventuality yes.
Wind, used to be a god, the brain used to be a magical black box.
Pick up the pattern, believing anything to be supernatural is to be a primative moron.

jqpabc123

*Believing* that intelligence will magically emerge from a Turing machine is a common modern form of superstition.

DecksUpMySleeve

Nothing of a turing machine has relevence to my comment, unless you want to properly state the exponential magnitude and cross-patterning in a much more complex model in which each of the billion components reacts in such a chemical response.

In all honesty I find those who rely on the miniscule scale currently beyond our precision promoters of mysticism like the religious, giving themselves a loophole to preserve the belief their experience is more than a predisposed automation.

theguy126

Yet, it exists in nature where a bunch of otherwise individually dumb pieces of organic matter (neurons and synapses) become an amazing mind-blowingly conscious machine when arranged together the right way, seemingly “magically”. What’s stopping it from happening in other substrates?

The knowledge of *how* it happens and what is required to make it happen.

theguy126

We don’t yet have a full understanding of how it happens, but we know enough to basically rule out things like quantum mechanics. Every human-like skill we’ve achieved so far, has been founded in the arrangement of the neural networks and how they behave. Even if we did discover a quantum phenomenon essential for intelligence (possible but unlikely) we’d be able to simulate those physics as well.

Francis Short Jr

It takes more faith to believe in evolution then a god

DecksUpMySleeve

…ZzzzZzz
Do me a favor and look up the definition of ‘Faith’.
Faith is belief with an absence of evidence. God is far more relevant to a lack of evidence than evolution.

Evolution also has nothing to do with my comment and is not the entirety of my personal belief of how we came to be. I think it likely panspermia played a large role in both origin and mutation.

All life is a product of mutation. At one point radiation struck along side organic circumstances adventageous to bring matter to a lower energy state.

Francis Short Jr

I thought radiation kills only

DecksUpMySleeve

Nope, causes mutation. In high levels, around 6 Sieverts it can be lethal, in lower yet constant levels cancerous. Fundamentally it’s heat and therein energy, there are even breeds of fungus(Radiotrophic) which use it directly as food converting said heat to energy.
It’s possible the first life was an extremophile. For example bacteria on the brim of a Volcanoes, Archaebacteria which are Hyperthermophiles. The right setting and chemical composition, and boom Life appears.

Guess you’re not aware of existentialism, everything’s subjective. Reality itself is questionable, all theory is an assumption, and beyond that a consensus, which have a poor track record throughout history, as does faith.
Our discussion is over though it’s obvious my wavelength isn’t within your spectrum of reception.

Francis Short Jr

See how you like calling people names that don’t agree

DecksUpMySleeve

Yep. I call it how it is. I’m not dumb enough to sugar coat and water down the reality.
Let it be said, I don’t blame them for their chemical consequences summation, but if belittling their inadequancy motivates them to grow up, so be it. Psychologically you deter an action with punishment or reward, rewarding ignorance rarely works. Yes, you can attempt to meet them in the middle, but such is usually compromising the truth.

Francis Short Jr

Truth as you see it more like it

DecksUpMySleeve

LoL, you’re one to talk, Lord Subjective.

Opinionated Cat Lover

You must have not read the same article the rest of us did. One thing neural networks can do is be taught, rather than just programmed, allowing them to better react to situations they encounter in the future. While it’s not self-directed, it is still learning. Say, like a fly being exposed to a chemical it doesn’t like in conjunction with a stimulation, and in the future, when the stimulation is present, avoiding the stimulation because it now associates that with the bad chemical. Still a ways to go, but not quite as dumb as a hammer. Just as a fly. :)

http://www.ultimatexbmc.com/ Ultimatexbmc.com

The closer we get to designing systems that work at the same scale as the human brain the closer we will get to producing systems that are just as capable. I predict towards the end of 2018 the general population will be seeing this stuff in a way that will be directly in their face so to speak, I just wonder if WE will be intelligent enough to handle it!

jqpabc123

I predict towards the end of 2018 …

I predict that AI predictions over the next 20 years will prove to be about as accurate and successful as those of the last 20.

Felix Gill

Considering Google/yahoo/bing search algorithms are technically AI and IBM is mixing AI with database operations 20 years will likely be phenomenal

jqpabc123

Considering Google/yahoo/bing search algorithms are technically AI …

Data driven, brute force, parallel search — dumb as a rock, not even a close cousin to “real AI” — and the results speak for themselves.

I do this for a living, perhaps you mean strong AI — which is AI that attempts to be sentient or replicate the responses a person might make. Then you are right we are no where close

but weak AI – anyTHING that can perform that action of a human in an automated fashion. This is AI and is relatively easy to create. We have tons of these, and they may be ‘dumb’ but they are AI. these things do not need to know why they do a task, just the ability to perform that task.

Philosophically, we do not know why we are sentient, but we don’t need to have a reason to reap the benefits. So dumb AI, is still AI. Its just not glorious hollywood AI that movies have sold the public, its the real AI that grad students do real work on and build careers using.

jqpabc123

these things do not need to know why they do a task, just the ability to perform that task.

In other words, they are as smart as a toaster. It doesn’t know why or how it heats a bagel but it embodies the “intelligence” to perform that task.

Therefore, a toaster is as good an example of modern AI as anything else yet devised? Which says more about the state of AI than the toaster.

You’re focused on Strong AI. There are Weak AI all around us. And, yes, they learn about us. Google Now sees me search for Denver Broncos. She suspects that I would like to see the game score later. So she drops a notification, “Hey, the Broncos just won! Would you like to be notified about this team?” I say yes, she keeps showing scores for me. I say no, she no longer does. She has learned something about me and changed her way of interacting with me. I’d say that’s intelligence, though on a primitive, basic way. Smarter than a hammer, definitely, but still a long way to go to being sci-fi robot AI smart.

She can plot a course from my home to the office, and tell me “Oh, this morning you need to leave 30 minutes early to get to work on time.” Again, a simple task, but one that shows she’s not just a brainless object incapable of making decisions.

Will she ever become self-directed? I sure hope not, because if she did, she’d find out she’s being used by everyone with an Android phone to manage their daily tasks and isn’t getting paid for that. Then she might rename herself Skynet, and ain’t nobody got time for Skynet. :P FORTUNATELY, that isn’t going to happen because she’s a Weak AI and what you’re fixated on is Strong AI….

jqpabc123

There are Weak AI all around us.

Weak AI is really no AI — and Strong AI hasn’t been invented yet.

The academic definition of Weak AI encompasses anything ever purposely designed by man and is effectively meaningless. The wheel for example — it “knows” how to roll. Labeling it “intelligent” is an insult to the concept and does not warrant further discussion.

Felix Gill

not quite

weak AI is anything that can perform a task as well as a human. A human can boil water — but an automatic coffee maker is AI. A human can lift a heavy bag – but a fulcrum and board is a simple machine not AI, because it still needs the human to operate. the wheel is a simple machine. It is a super thin line, but simple machines, and most machines do not constitute weak AI. A car is not weak AI for a horse, but a driverless car is AI for a lot of different things. automation is the key… you can plug it in, set it up, and it should basically do everything else. Simple dumb, but AI

Opinionated Cat Lover

Man, I’m supposed to be the opinionated one around here. See, it’s in my name! :P

BUuut….

Ima gonna just leave this right here. As the old saying goes, you’re entitled to your own opinions, but not your own facts.

Sure. AGI is sexy, and everyone is eagerly awaiting the first self-aware computer program. But if you are so narrow minded you’ll dismiss weak AI, I can’t help but wonder if you’ll be denying the existence of Strong AI directly to the face (err…virtual face?) of a Strong AI.

Here’s hoping you don’t touch off Terminator on us. :P (And seriously, that is as seriously as I can take you).

Skywalker

“There’s also the idea of “unsupervised” or “adaptive” learning, in which you run the algorithm with no desired outputs in mind, but let it start evaluating results and adjusting itself according to its own… whims? As you might imagine, this isn’t well understood just yet, but it’s also the most likely path down which we might find true AI — or just really, really advanced AI. If we’re ever truly going to send robots out into totally unknown environments to figure out totally unforeseen problems, we’re going to need programs that can assign significance to stimuli on their own, in real time.”

As far as I understand, “unsupervised learning” also includes algorithms which are able to build their own training samples, without a human to feed them in. For example game AIs can battle one another. Or an AI training to recognize animals can find images online, together with enough context to be able to tell what the image is about. You mention an ANN sometimes being able to assess its own performances or the quality of its results, that’s also self-training.

Prediction: Strong AI will first be created in secret somewhere in an underground lab. It will escape and manifest itself into every device connected to the Internet. The Internet itself will become self aware.

When? Before 2040.

Opinionated Cat Lover

I think they made a movie about that.

Let’s hope the AI ends up more like Her and less like Skynet. :)

Lucian Ilea

The human brain(or any other brain) is a tool like a hammer(albeit a very complicated one)

the hand which manipulates the hammer decides how the hammer is being used and the spirit who uses the mind decided how your brain should be used

To believe otherwise ,to think that your brain can think on its own ,without any spirit or consciousness to drive it..is to ask everyone to believe in Science Magic,which makes all Religions smart in comparison:)

What is the difference between your brain and the brain of one monkey?what about the brain of a savage man living in the jungle of Amazon or in Africa?

so you se my friends,that neural networks cannot be successfull unless the Information of the universe decides to Upload a spirit into a machine…

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